In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated patient data to extract information. This review offers a historical perspective and describes the potential clinical benefits from research and applications in this field, as well as significant obstacles to adoption. Best practices for implementing computational pathology workflows are presented. These include infrastructure considerations, acquisition of training data, quality assessments, as well as regulatory, ethical, and cyber-security concerns. Recommendations are provided for regulators, vendors, and computational pathology practitioners in order to facilitate progress in the field. (c) 2019 The Authors. The Journal of Pathology published by John Wiley amp; Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Alzheimers disease (AD) is an incurable, progressive and devastating neurodegenerative disease. Pathogenesis of AD is associated with the aggregation and accumulation of amyloid beta (A & beta;), a major neurotoxic mediator that triggers neuroinflammation and memory impairment. Recently, we found that cellulose ether compounds (CEs) have beneficial effects against prion diseases by inhibiting protein misfolding and replication of prions, which share their replication mechanism with A & beta;. CEs are FDA-approved safe additives in foods and pharmaceuticals. Herein, for the first time we determined the therapeutic effects of the representative CE (TC-5RW) in AD using in vitro and in vivo models. Our in vitro studies showed that TC-5RW inhibits A & beta; aggregation, as well as neurotoxicity and immunoreactivity in A & beta;-exposed human and murine neuroblastoma cells. In in vivo studies, for the first time we observed that single and weekly TC-5RW administration, respectively, improved memory functions of transgenic 5XFAD mouse model of AD. We further demonstrate that TC-5RW treatment of 5XFAD mice significantly inhibited A & beta; oligomer and plaque burden and its associated neuroinflammation via regulating astrogliosis, microgliosis and proinflammatory mediator glial maturation factor beta (GMF & beta;). Additionally, we determined that TC-5RW reduced lipopolysaccharide-induced activated gliosis and GMF & beta; in vitro. In conclusion, our results demonstrate that CEs have therapeutic effects against A & beta; pathologies and cognitive impairments, and direct, potent anti-inflammatory activity to rescue neuroinflammation. Therefore, these FDA-approved compounds are effective candidates for developing therapeutics for AD and related neurodegenerative diseases associated with protein misfolding.

Objective—

Pathological neovascularization is crucial for progression and morbidity of serious diseases such as cancer, diabetic retinopathy, and age-related macular degeneration. While mechanisms of ongoing pathological neovascularization have been extensively studied, the initiating pathological vascular remodeling (PVR) events, which precede neovascularization remains poorly understood. Here, we identify novel molecular and cellular mechanisms of preneovascular PVR, by using the adult choriocapillaris as a model.

Approach and Results—

Using hypoxia or forced overexpression of VEGF (vascular endothelial growth factor) in the subretinal space to induce PVR in zebrafish and rats respectively, and by analyzing choriocapillaris membranes adjacent to choroidal neovascular lesions from age-related macular degeneration patients, we show that the choriocapillaris undergo robust induction of vascular intussusception and permeability at preneovascular stages of PVR. This PVR response included endothelial cell proliferation, formation of endothelial luminal processes, extensive vesiculation and thickening of the endothelium, degradation of collagen fibers, and splitting of existing extravascular columns. RNA-sequencing established a role for endothelial tight junction disruption, cytoskeletal remodeling, vesicle- and cilium biogenesis in this process. Mechanistically, using genetic gain- and loss-of-function zebrafish models and analysis of primary human choriocapillaris endothelial cells, we determined that HIF (hypoxia-induced factor)-1α-VEGF-A-VEGFR2 signaling was important for hypoxia-induced PVR.

Conclusions—

Our findings reveal that PVR involving intussusception and splitting of extravascular columns, endothelial proliferation, vesiculation, fenestration, and thickening is induced before neovascularization, suggesting that identifying and targeting these processes may prevent development of advanced neovascular disease in the future.

Visual Overview—

An online visual overview is available for this article.

Background

Tumor-associated macrophages (TAMs) constitute a subset of nonneoplastic cells in tumor stroma and influence cancer progression in solid tumors. The clinical significance of TAMs in urinary bladder cancer(UBC) is controversial.

Methods

We prospectively studied 103 patients with stage pT1–T4 UBC treated with cystectomy and pelvic lymph node dissection. Tumor sections were immunostained with M2-specific macrophage marker CD163 and proliferation marker Ki-67. The expression of these markers in cancer cells as well as macrophage infiltration (MI) in tumor stroma was analyzed in relation to clinical data and outcome.

Results

The mean rate of CD163 and Ki-67 expressed by cancer cells were 35% and 78%, respectively. With borderline significance, MI was associated with lower rate of lymph node metastasis (P = 0.06). CD163 expression in cancer cells was proportional to MI (P<0.014). Patients with CD163-positive tumors and strong MI had significantly longer cancer-specific survival (CSS) (76 months), compared to patient with CD163-positive tumors and weak MI (28 months) (P = 0.02).

Conclusions

M2-specific MI tends to be inversely correlated with LN metastasis and improved CSS in UBC. MI might have protective impact in CD163-positive tumors. Expression of CD163 in cancer cells is significantly correlated with MI and might have a tumor promoting impact.

Purpose: We investigated the effects of alterations in the biological markers p14, p53, p21, and p16 in relation to tumour cell proliferation, T-category, N- category, lymphovascular invasion, and the ability to predict prognosis in patients with muscle-invasive bladder cancer (MIBC) treated with cystectomy and, if applicable, chemotherapy.

Materials and methods: We prospectively studied patients with urinary bladder cancer pathological stage pT1 to pT4 treated with cystectomy, pelvic lymph node dissection and postoperative chemotherapy. Tissue microarrays from paraffin-embedded cystectomy tumour samples were examined for expression of immunostaining of p14, p53, p21, p16 and Ki-67 in relation to other clinical and pathological factors as well as cancer-specific survival.

Results: The median age of the 110 patients was 70 years (range 51-87 years), and 85 (77%) were male. Pathological staging was pT1 to pT2 (organ-confined) in 28 (25%) patients and pT3 to pT4 (non-organ-confined) in 82 (75%) patients. Lymph node metastases were found in 47 patients (43%). P14 expression was more common in tumours with higher T-stages (P = 0.05). The expression of p14 in p53 negative tumours was associated with a significantly shorter survival time (P=0.003). Independently of p53 expression, p14 expression was associated with an impaired response to chemotherapy (P=0.001). The expression of p21 in p53 negative tumours was associated with significantly decrease levels of tumour cell proliferation detected as Ki-67 expression (P=0.03).

Conclusions: The simultaneous expression of the senescence markers involved in the p53-pathway shows a more relevant correlation to the pathological outcome of MIBC than each protein separately. P14 expression in tumours with non-altered (p53-) tumours is associated with poor prognosis. P14 expression is associated with impaired response to chemotherapy. P21 expression is related to decreased tumour cell proliferation.

OBJECTIVES: To investigate the possibility of detecting sentinel lymph nodes (SNs) in patients with urinary bladder cancer (BCa) intra-operatively and whether the histopathological status of the identified SNs reflected that of the lymphatic field.

PATIENTS AND METHODS: We studied 103 patients with BCa pathological stage T1-T4 who were treated with cystectomy and pelvic lymph node (LN) dissection during 2005-2011 at the Department of Urology, Linköping University Hospital. Radioactive tracer Nanocoll 70 MBq and blue dye were injected into the bladder wall around the primary tumour before surgery. SNs were detected ex vivo during the operation with a handheld Geiger probe (Gamma Detection System; Neoprobe Corp., Dublin, OH, USA). All LNs were formalin-fixed, sectioned three times, mounted on slides and stained with haematoxylin and eosin. An experienced uropathologist evaluated the slides.

RESULTS: The mean age of the patients was 69 years, and 80 (77%) were male. Pathological staging was T1-12 (12%), T2-20 (19%), T3-48 (47%) and T4-23 (22%). A mean (range) number of 31 (7-68) nodes per patient were examined, totalling 3 253 nodes. LN metastases were found in 41 patients (40%). SNs were detected in 83 of the 103 patients (80%). Sensitivity and specificity for detecting metastatic disease by SN biopsy (SNB) varied between LN stations, with average values of 67% and 90%, respectively. LN metastatic density (LNMD) had a significant prognostic impact; a value of ≥8% was significantly related to shorter survival. Lymphovascular invasion (LVI) occurred in 65% of patients (n = 67) and was significantly associated with shorter cancer-specific survival (P < 0.001).

CONCLUSION: We conclude that SNB is not a reliable technique for peri-operative localization of LN metastases during cystectomy for BCa; however, LNMD has a significant prognostic value in BCa and may be useful in the clinical context and in BCa oncological and surgical research. LVI was also found to be a prognostic factor.

Purpose: To investigate the association between p53 expression in tumor cells and intratumoral macrophage infiltration in muscle-invasive urinary bladder cancer (MIBC) in relation to clinical and pathological variables and outcomes after radical cystectomy. Methods: Tumor specimens of the primary tumor from patients treated with radical cystectomy for MIBC were immunostained with the M2-macrophage-specific marker CD163 and the cell cycle protein p53. The expression of these markers was analyzed in relation to patients and tumor characteristics and outcome. Results: Out of 100 patients with urinary bladder cancer (UBC) pathological stage T1-4 N0-3 M0, 77% were men. The patients had a median age of 69 years and 80% had nonorgan-confined tumors (pT3-4). Lymph node metastasis was found in 42 (42%) of all patients. P53-positive expressions were found in 63 (63%) patients. Strong macrophage infiltration in the tumor microenvironment was shown in 74 (74%) patients. Combinations of CD163/p53 status were as follows: CD163+/p53+, 50%; CD163+/p53-, 24%; CD163-/p53+, 13%; and CD163-/p53-, 13%. Patients with CD163+/P53+ had higher proportions of organ-confined tumors. Conclusions: In the present series of patients with MIBC treated with cystectomy, we found that high CD163+ macrophage infiltration in the tumor micro-environment often was combined with p53+ cancer cells. This simultaneous expression of p53 by tumor cells and increased infiltration of M2-macrophages in the tumor microenvironment was associated with improved CSS, which might indicate a possible protective effect of M2 macrophages in p53+ tumors. Further investigations are needed to explore the biological relation between mutational burden and immune profile in MIBC. (c) 2022 Published by Elsevier Inc.

Systemic autoimmune rheumatic disorders (SARD) represent important causes of morbidity and mortality in humans. The mechanisms triggering autoimmune responses are complex and involve a network of genetic factors. Mercury-induced autoimmunity (HgIA) in mice is an established model to study the mechanisms of the development of antinuclear antibodies (ANA), which is a hallmark in the diagnosis of SARD. A.SW mice with HgIA show a significantly higher titer of antinucleolar antibodies (ANoA) than the B10.S mice, although both share the same MHC class II (H-2). We applied a genome-wide association study (GWAS) to their Hg-exposed F2 offspring to investigate the non-MHC genes involved in the development of ANoA. Quantitative trait locus (QTL) analysis showed a peak logarithm of odds ratio (LOD) score of 3.05 on chromosome 3. Microsatellites were used for haplotyping, and fine mapping was conducted with next generation sequencing. The candidate genes Bank1 (B-cell scaffold protein with ankyrin repeats 1) and Nfkbl (nuclear factor kappa B subunit 1) were identified by additional QTL analysis. Expression of the Bank1 and Nfkb1 genes and their downstream target genes involved in the intracellular pathway (Tlr9,II6, Tnf) was investigated in mercury-exposed A.SW and B10.S mice by real-time PCR. Bank1 showed significantly lower gene expression in the A.SW strain after Hg-exposure, whereas the B10.S strain showed no significant difference. Nfkb1, Tlr9, II6 and Tnf had significantly higher gene expression in the A.SW strain after Hg-exposure, while the B10.S strain showed no difference. This study supports the roles of Bank1 (produced mainly in B-cells) and Nfkbl (produced in most immune cells) as key regulators of ANoA development in HgIA.

Background Pancreatic cancer is an aggressive malignancy and a leading cause of cancer death worldwide; its lethality is partly linked to the difficulty of early diagnosis. Modern devices for endoscopic ultrasound-guided fine-needle biopsy (EUS-FNB) were recently developed to improve targeting and sampling of small lesions, but innovative technologies for microscopic assessment are still lacking. Ex vivo fluorescence confocal laser microscopy (FCM) is a new digital tool for real-time microscopic assessment of fresh unfixed biological specimens, avoiding conventional histological slide preparation and potentially being highly appealing for EUS-FNB specimens. Methods This study evaluated the possible role of FCM for immediate evaluation of pancreatic specimens from EUS-FNB. It involved comparison of the interobserver agreement between the new method and standard histological analysis during international multicenter sharing of digital images. Digital images from 25 cases of EUS-FNB obtained with real-time FCM technology and 25 paired digital whole-slide images from permanent conventional paraffin sections were observed by 10 pathologists from different Institutions in Europe, Japan, and the United States, in a blinded manner. The study evaluated 500 observations regarding adequacy, morphological clues, diagnostic categories, and final diagnosis. Findings Statistical analysis showed substantial equivalence in the interobserver agreement among pathologists using the two techniques. There was also good inter-test agreement in determining sample adequacy and when assigning a diagnostic category. Among morphological features, nuclear enlargement was the most reproducible clue, with very good inter-test agreement. Interpretation Findings in this study are from international multicenter digital sharing and are published here for the first time. Considering the advantages of FCM digital diagnostics in terms of reduced time and unaltered sample maintenance, the ex vivo confocal laser microscopy may effectively improve traditional EUS-FNB diagnostics, with significant implications for planning modern diagnostic workflow for pancreatic tumors. Copyright (c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.

Exposure to heavy metals may have toxic effects on several human organs causing morbidity and mortality. Metals may trigger or exacerbate autoimmunity in humans. Inbred mouse strains with certain H-2 haplotypes are susceptible to xenobiotic-induced autoimmunity; and their immune response to metals such as mercury, gold, and silver have been explored. Serum antinuclear antibodies (ANA), polyclonal B-cell activation, hypergammaglobulinemia and tissue immune complex deposition are the main features of metal-induced autoimmunity in inbred mice. However, inbred mouse strains do not represent the genetic heterogeneity in humans. In this study, outbred Swiss Webster (SW) mice exposed to gold or mercury salts showed immune and autoimmune responses. Intramuscular injection of 22.5 mg/kg.bw aurothiomalate (AuTM) induced IgG ANA in SW mice starting after 5 weeks that persisted until week 15 although with a lower intensity. This was accompanied by elevated serum levels of total IgG antibodies against chromatin and total histones. Exposure to gold led to development of serum IgG autoantibodies corresponding to H1 and H2A histones, and dsDNA. Both gold and mercury induced polyclonal B-cell activation. Eight mg/L mercuric chloride (HgCl2) in drinking water, caused IgG antinucleolar antibodies (ANoA) after 5 weeks in SW mice accompanied by immune complex deposition in kidneys and spleen. Serum IgG antibodies corresponding to anti-fibrillarin, and anti-PM/Scl-100 antibodies, were observed in mercury-exposed SW mice. Gold and mercury trigger systemic autoimmune response in genetically heterogeneous outbred SW mice and suggest them as an appropriate model to study xenobiotic-induced autoimmunity.

Limited studies on whole slide imaging (WSI) in surgical neuropathology reported a perceived limitation in the recognition of mitoses. This study analyzed and compared the inter- and intra-observer concordance for atypical meningioma, using glass slides and WSI. Two neuropathologists and two residents assessed the histopathological features of 35 meningiomas-originally diagnosed as atypical-in a representative glass slide and corresponding WSI. For each histological parameter and final diagnosis, we calculated the inter- and intra-observer concordance in the two viewing modes and the predictive accuracy on recurrence. The concordance rates for atypical meningioma on glass slides and on WSI were 54% and 60% among four observers and 63% and 74% between two neuropathologists. The inter-observer agreement was higher using WSI than with glass slides for all parameters, with the exception of high mitotic index. For all histological features, we found median intra-observer concordance of &gt;= 79% and similar predictive accuracy for recurrence between the two viewing modes. The higher concordance for atypical meningioma using WSI than with glass slides and the similar predictive accuracy for recurrence in the two modalities suggest that atypical meningioma may be safely diagnosed using WSI.

Alzheimers disease (AD) is a neurodegenerative disorder characterized by a progressive loss of multiple cognitive functions. Accumulation of amyloid beta oligomers (oA beta) play a major role in the neurotoxicity associated with the disease process. One of the early affected brain regions is the hippocampus, wherein a reduction of the vacuolar protein sorting-associated protein 35 (VPS35), the core protein comprising the retromer complex involved in cellular cargo sorting, has been identified. To investigate the role of the retromer function on the accumulation and clearance of oA beta, we reduced retromer function by selectively inhibiting VPS35 gene expression using siRNA in differentiated neuronal SH-SY5Y cells. As cell-to-cell transfer of oA beta to new brain regions is believed to be important for disease progression we investigated the effect of VPS35 reduction both in cells with direct uptake of oA beta and in cells receiving oA beta from donor cells. We demonstrate that reduced retromer function increases oA beta accumulation in both cell systems, both the number of cells containing intracellular oA beta and the amount within them. This effect was shown at different time points and regardless if the AD originated from the extracellular milieu or via a direct neuronal cell-to-cell transfer. Interestingly, not only did reduced VPS35 cause oA beta accumulation, but oA beta treatment alone also lead to a reduction of VPS35 protein content. The accumulated oA beta seems to co-localize with VPS35 and early endosome markers. Together, these findings provide evidence that reduced retromer function decreases the ability for neurons to transport and clear neurotoxic oA beta received through different routes resulting in the accumulation of oA beta. Thus, enhancing retromer function may be a potential therapeutic strategy to slow down the pathophysiology associated with the progression of AD.

Although neutrophil extracellular traps (NETs) have been highlighted in several systemic inflammatory diseases, their clinical correlates and potential pathological role remain obscure. Herein, we describe a dramatic onset of systemic lupus erythematosus (SLE) with clear-cut pathogenic implications for neutrophils and NET formation in a young woman with cardiac (Libman-Sacks endocarditis) and central nervous system (psychosis and seizures) involvement. Despite extensive search, circulating antiphospholipid autoantibodies, a hallmark of Libman-Sacks endocarditis, could not be detected. Instead, we observed active NET formation in the tissue of the mitral valve, as well as in the circulation. Levels of NET remnants were significantly higher in serially obtained sera from the patient compared with sex-matched blood donors (p=.0011), and showed a non-significant but substantial correlation with blood neutrophil counts (r=0.65, p=.16). The specific neutrophil elastase activity measured in serum seemed to be modulated by the provided immunosuppressive treatment. In addition, we found anti-Ro60/SSA antibodies in the cerebrospinal fluid of the patient but not NET remnants or increased elastase activity. This case illustrates that different disease mechanisms mediated via autoantibodies can occur simultaneously in SLE. NET formation with release of cytotoxic NET remnants is a candidate player in the pathogenesis of this non-canonical form of Libman-Sacks endocarditis occurring in the absence of traditional antiphospholipid autoantibodies. The case description includes longitudinal results with clinical follow-up data and a discussion of the potential roles of NETs in SLE.

Artificial intelligence as a medical device is increasingly being applied to healthcare for diagnosis, risk stratification and resource allocation. However, a growing body of evidence has highlighted the risk of algorithmic bias, which may perpetuate existing health inequity. This problem arises in part because of systemic inequalities in dataset curation, unequal opportunity to participate in research and inequalities of access. This study aims to explore existing standards, frameworks and best practices for ensuring adequate data diversity in health datasets. Exploring the body of existing literature and expert views is an important step towards the development of consensus-based guidelines. The study comprises two parts: a systematic review of existing standards, frameworks and best practices for healthcare datasets; and a survey and thematic analysis of stakeholder views of bias, health equity and best practices for artificial intelligence as a medical device. We found that the need for dataset diversity was well described in literature, and experts generally favored the development of a robust set of guidelines, but there were mixed views about how these could be implemented practically. The outputs of this study will be used to inform the development of standards for transparency of data diversity in health datasets (the STANDING Together initiative). A systematic review, combined with a stakeholder survey, presents an overview of current practices and recommendations for dataset curation in health, with specific focuses on data diversity and artificial intelligence-based applications.

Purpose Evaluate the prediction of quantitative coronary angiography (QCA) values from MPI, by means of deep learning. Methods 546 patients (67% men) undergoing stress 99mTc-tetrofosmin MPI in a CZT camera in the upright and supine position were included (1092 MPIs). Patients were divided into two groups: ICA group included 271 patients who performed an ICA within 6 months of MPI and a control group with 275 patients with low pre-test probability for CAD and a normal MPI. QCA analyses were performed using radiologic software and verified by an expert reader. Left ventricular myocardium was segmented using clinical nuclear cardiology software and verified by an expert reader. A deep learning model was trained using a double cross-validation scheme such that all data could be used as test data as well. Results Area under the receiver-operating characteristic curve for the prediction of QCA, with &gt; 50% narrowing of the artery, by deep learning for the external test cohort: per patient 85% [95% confidence interval (CI) 84%-87%] and per vessel; LAD 74% (CI 72%-76%), RCA 85% (CI 83%-86%), LCx 81% (CI 78%-84%), and average 80% (CI 77%-83%). Conclusion Deep learning can predict the presence of different QCA percentages of coronary artery stenosis from MPIs.

Limited evidence has shed light on how aSYN proteins affect the oligodendrocyte phenotype and pathogenesis in synucleinopathies that include Parkinsons disease (PD) and multiple system atrophy (MSA). Here, we investigated early transcriptomic changes within PD and MSA O4(+) oligodendrocyte lineage cells (OLCs) generated from patient-induced pluripotent stem cells (iPSCs). We found impaired maturation of PD and MSA O4(+) OLCs compared to controls. This phenotype was associated with changes in the human leukocyte antigen (HLA) genes, the immunoproteasome subunit PSMB9, and the complement component C4b for aSYN p.A53T and MSA O4(+) OLCs, but not in SNCA(trip) O4(+) OLCs despite high levels of aSYN assembly formation. Moreover, SNCA overexpression resulted in the development of O4(+) OLCs, whereas exogenous treatment with aSYN species led to significant toxicity. Notably, transcriptome profiling of genes encoding proteins forming Lewy bodies and glial cytoplasmic inclusions revealed clustering of PD aSYN p.A53T O4(+) OLCs with MSA O4(+) OLCs. Our work identifies early phenotypic and pathogenic changes within human PD and MSA O4(+) OLCs.

The tumour microenvironment has been shown to be a valuable source of prognostic information for different cancer types. This holds in particular for triple negative breast cancer (TNBC), a breast cancer subtype for which currently no prognostic biomarkers are established. Although different methods to assess tumour infiltrating lymphocytes (TILs) have been published, it remains unclear which method (marker, region) yields the most optimal prognostic information. In addition, to date, no objective TILs assessment methods are available. For this proof of concept study, a subset of our previously described TNBC cohort (n = 94) was stained for CD3, CD8 and FOXP3 using multiplex immunohistochemistry and subsequently imaged by a multispectral imaging system. Advanced whole-slide image analysis algorithms, including convolutional neural networks (CNN) were used to register unmixed multispectral images and corresponding H&E sections, to segment the different tissue compartments (tumour, stroma) and to detect all individual positive lymphocytes. Densities of positive lymphocytes were analysed in different regions within the tumour and its neighbouring environment and correlated to relapse free survival (RFS) and overall survival (OS). We found that for all TILs markers the presence of a high density of positive cells correlated with an improved survival. None of the TILs markers was superior to the others. The results of TILs assessment in the various regions did not show marked differences between each other. The negative correlation between TILs and survival in our cohort are in line with previous studies. Our results provide directions for optimizing TILs assessment methodology. (C) 2021 The Author(s). Published by Elsevier Ltd.

As part of routine histological grading, for every invasive breast cancer the mitotic count is assessed by counting mitoses in the (visually selected) region with the highest proliferative activity. Because this procedure is prone to subjectivity, the present study compares visual mitotic counting with deep learning based automated mitotic counting and fully automated hotspot selection. Two cohorts were used in this study. Cohort A comprised 90 prospectively included tumors which were selected based on the mitotic frequency scores given during routine glass slide diagnostics. This pathologist additionally assessed the mitotic count in these tumors in whole slide images (WSI) within a preselected hotspot. A second observer performed the same procedures on this cohort. The preselected hotspot was generated by a convolutional neural network (CNN) trained to detect all mitotic figures in digitized hematoxylin and eosin (Hamp;E) sections. The second cohort comprised a multicenter, retrospective TNBC cohort (n = 298), of which the mitotic count was assessed by three independent observers on glass slides. The same CNN was applied on this cohort and the absolute number of mitotic figures in the hotspot was compared to the averaged mitotic count of the observers. Baseline interobserver agreement for glass slide assessment in cohort A was good (kappa 0.689; 95% CI 0.580-0.799). Using the CNN generated hotspot in WSI, the agreement score increased to 0.814 (95% CI 0.719-0.909). Automated counting by the CNN in comparison with observers counting in the predefined hotspot region yielded an average kappa of 0.724. We conclude that manual mitotic counting is not affected by assessment modality (glass slides, WSI) and that counting mitotic figures in WSI is feasible. Using a predefined hotspot area considerably improves reproducibility. Also, fully automated assessment of mitotic score appears to be feasible without introducing additional bias or variability.

Much research has focused on finding novel prognostic biomarkers for triple negative breast cancer (TNBC), whereas only scattered information about the relation between histopathological features and survival in TNBC is available. This study aims to explore the prognostic value of histological subtypes in TNBC. A multicenter retrospective TNBC cohort was established from five Dutch hospitals. All non-neoadjuvantly treated, stage I-III patients with estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 negative breast cancer diagnosed between 2006 and 2014 were included. Clinical and follow-up data (overall survival; OS, relapse free survival; RFS) were retrieved and a central histopathological review was performed. Of 597 patients included (median follow up 62.8 months, median age at diagnosis 56.0 years), 19.4% developed a recurrence. The most prevalent histological subtypes were carcinoma of no special type (NST) (88.4%), metaplastic carcinoma (4.4%) and lobular carcinoma (3.4%). Collectively, tumors of special type were associated with a worse RFS and OS compared to carcinoma NST (RFS HR 1.89; 95% CI 1.18-3.03; p = 0.008; OS HR 1.94; 95% CI 1.28-2.92; p = 0.002). Substantial differences in survival, however, were present between the different histological subtypes. In the presented TNBC cohort, special histological subtype was in general associated with less favorable survival. However, within the group of tumors of special type there were differences in survival between the different subtypes. Accurate histological examination can provide specific prognostic information that may potentially enable more personalized treatment and surveillance regimes for TNBC patients.

Artificial intelligence (AI) holds much promise for enabling highly desired imaging diagnostics improvements. One of the most limiting bottlenecks for the development of useful clinical-grade AI models is the lack of training data. One aspect is the large amount of cases needed and another is the necessity of high-quality ground truth annotation. The aim of the project was to establish and describe the construction of a database with substantial amounts of detail-annotated oncology imaging data from pathology and radiology. A specific objective was to be proactive, that is, to support undefined subsequent AI training across a wide range of tasks, such as detection, quantification, segmentation, and classification, which puts particular focus on the quality and generality of the annotations. The main outcome of this project was the database as such, with a collection of labeled image data from breast, ovary, skin, colon, skeleton, and liver. In addition, this effort also served as an exploration of best practices for further scalability of high-quality image collections, and a main contribution of the study was generic lessons learned regarding how to successfully organize efforts to construct medical imaging databases for AI training, summarized as eight guiding principles covering team, process, and execution aspects.

Copper (Cu) is essential for living organisms, and acts as a cofactor in many metabolic enzymes. To avoid the toxicity of free Cu, organisms have specific transport systems that 'chaperone' the metal to targets. Cancer progression is associated with increased cellular Cu concentrations, whereby proliferative immortality, angiogenesis and metastasis are cancer hallmarks with defined requirements for Cu. The aim of this study is to gather all known Cu-binding proteins and reveal their putative involvement in cancers using the available database resources of RNA transcript levels. Using the database along with manual curation, we identified a total of 54 Cu-binding proteins (named the human Cu proteome). Next, we retrieved RNA expression levels in cancer versus normal tissues from the TCGA database for the human Cu proteome in 18 cancer types, and noted an intricate pattern of up- and downregulation of the genes in different cancers. Hierarchical clustering in combination with bioinformatics and functional genomics analyses allowed for the prediction of cancer-related Cu-binding proteins; these were specifically inspected for the breast cancer data. Finally, for the Cu chaperone ATOX1, which is the only Cu-binding protein proposed to have transcription factor activities, we validated its predicted over-expression in patient breast cancer tissue at the protein level. This collection of Cu-binding proteins, with RNA expression patterns in different cancers, will serve as an excellent resource for mechanistic-molecular studies of Cu-dependent processes in cancer.

Copper plays a key role in cancer metastasis, which is the most common cause of cancer death. Copper depletion treatment with tetrathiomolybdate (TM) improved disease-free survival in breast cancer patients with high risk of recurrence in a phase II clinical trial. Because the copper metallochaperone ATOX1 was recently reported to drive breast cancer cell migration and breast cancer migration is a critical factor in metastasis, we tested if ATOX1 expression levels in primary tumor tissue could predict the TM treatment outcome of breast cancer patients at high risk of recurrence. We performed ATOX1 immunohistochemical staining of breast tumor material (before TM treatment) of 47 patients enrolled in the phase II TM clinical trial and evaluated ATOX1 expression levels in relation with patient outcome after TM treatment. Our results show that higher ATOX1 levels in the tumor cell cytoplasm correlate with a trend towards better event-free survival after TM treatment for triple-negative breast cancer patients and patients at stage III of disease. In conclusion, ATOX1 may be a potential predictive biomarker for TM treatment of breast cancer patients at high risk of recurrence and should be tested in a larger cohort of patients.

Rectal cancer is treated with preoperative radiotherapy (RT) to downstage the tumor, reduce local recurrence, and improve patient survival. Still, the treatment outcome varies significantly and new biomarkers are desired. Collagen I (Col-I) is a potential biomarker, which can be visualized label-free by second harmonic generation (SHG). Here, we used SHG to identify Col-I changes induced by RT in surgical tissue, with the aim to evaluate the clinical significance of RT-induced Col-I changes. First, we established a procedure for quantitative evaluation of Col-I by SHG in CDX2-stained tissue sections. Next, we evaluated Col-I properties in material from 31 non-RT and 29 RT rectal cancer patients. We discovered that the Col-I intensity and anisotropy were higher in the tumor invasive margin than in the inner tumor and normal mucosa, and RT increased and decreased the intensity in inner tumor and normal mucosa, respectively. Furthermore, higher Col-I intensity in the inner tumor was related to increased distant recurrence in the non-RT group but to longer survival in the RT group. In conclusion, we present a new application of SHG for quantitative analysis of Col-I in surgical material, and the first data suggest Col-I intensity as a putative prognostic biomarker in rectal cancer. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License.

Pancreatic ductal adenocarcinoma (PDAC) has a bleak prognosis, especially for the majority of patients diagnosed with metastatic disease. The primary option for palliative treatment is chemotherapy, and responses beyond first-line treatment are rare and typically short. Here, we report a case of a 63-year-old woman with PDAC in the head of the pancreas who was initially successfully treated by pancreaticoduodenectomy followed by adjuvant chemotherapy with gemcitabine. However, disease recurrence with liver and para-aortic lymph node metastases was detected only two months after the completion of adjuvant chemotherapy. First-line palliative chemotherapy with gemcitabine-nab/paclitaxel was commenced. The results were discouraging, with disease progression (liver and lung metastases) detected at the first evaluation; the progression-free survival was just two months (64 days). Surprisingly, the response to second-line palliative chemotherapy with 5-fluorouracil-oxaliplatin was excellent; in combination with the ablation of a liver metastasis, this treatment regimen resulted in a complete radiological response and an 11-month treatment-free interval with a sustained good performance status.

In spite of recent diagnostic and therapeutic advances, the prognosis of pancreatic ductal adenocarcinoma (PDAC) remains very poor. As most patients are not amenable to curative intent treatments, optimized palliative management is highly needed. One key question is to what extent promising results produced by randomized controlled trials (RCTs) correspond to clinically meaningful outcomes in patients treated outside the strict frames of a clinical trial. To answer such questions, real-world evidence is necessary. The present paper reviews and discusses the current literature on first- and second-line palliative chemotherapy in PDAC. Notably, a growing number of studies report that the outcomes of the two predominant first-line multidrug regimens, i.e. gemcitabine plus nab-paclitaxel (GnP) and folfirinox (FFX), is similar in RCTs and real-life populations. Outcomes of second-line therapy following failure of first-line regimens are still dismal, and considerable uncertainty of the optimal management remains. Additional RCTs and real-world evidence studies focusing on the optimal treatment sequence, such as FFX followed by GnP or vice versa, are urgently needed. Finally, the review highlights the need for prognostic and predictive biomarkers to inform clinical decision making and enable personalized management in advanced PDAC.

Background

In recent years treatment options for advanced pancreatic cancer have markedly improved, and a combination regimen of gemcitabine and nab-paclitaxel is now considered standard of care in Sweden and elsewhere. Nevertheless, a majority of patients do not respond to treatment. In order to guide the individual patient to the most beneficial therapeutic strategy, simple and easily available prognostic and predictive markers are needed.

Methods

The potential prognostic value of a range of blood/serum parameters, patient-, and tumour characteristics was explored in a retrospective cohort of 75 patients treated with gemcitabine/nab-paclitaxel (Gem/NabP) for advanced pancreatic ductal adenocarcinoma (PDAC) in the South Eastern Region of Sweden. Primary outcome was overall survival (OS) while progression free survival (PFS) was the key secondary outcome.

Result

Univariable Cox regression analysis revealed that high baseline serum albumin (> 37 g/L) and older age (> 65) were positive prognostic markers for OS, and in multivariable regression analysis both parameters were confirmed to be independent prognostic variables (HR 0.48, p = 0.023 and HR = 0.47, p = 0.039,). Thrombocytopenia at any time during the treatment was an independent predictor for improved progression free survival (PFS) but not for OS (HR 0.49, p = 0.029, 0.54, p = 0.073), whereas thrombocytopenia developed under cycle 1 was neither related with OS nor PFS (HR 0.87, p = 0.384, HR 1.04, p = 0.771). Other parameters assessed (gender, tumour stage, ECOG performance status, myelosuppression, baseline serum CA19–9, and baseline serum bilirubin levels) were not significantly associated with survival.

Conclusion

Serum albumin at baseline is a prognostic factor with palliative Gem/NabP in advanced PDAC, and should be further assessed as a tool for risk stratification. Older age was associated with improved survival, which encourages further studies on the use of Gem/NabP in the elderly.

Background: Pancreatic cancer remains a leading cause of cancer-related death. To individualise management and improve survival, more accurate prognostic models are needed.Methods: All patients resected for pancreatic ductal adenocarcinoma in a tertiary Swedish centre during 2009-2019 were thoroughly analysed with regards to pathological and clinical parameters including tumour grade, resection margin status, para-aortic lymph node engagement (node station 16), and systemic treatment.Results: The study cohort included 275 patients. Overall median survival was 21.2 months (95% CI 17.5-24.8). Year of resection, margin status (R1 subdivided into R1(1mm)/R1(ink)), perineural invasion, differentiation grade, TNM stage, and adjuvant therapy were independent factors with significant impact on survival. Margin status also significantly affected recurrence-free survival and relapse patterns, with local and peritoneal relapses being associated with R1-status (p &lt; 0.001 and p = 0.007). Presence of paraaortic lymph node metastases was associated with shorter recurrence-free survival as compared to N1 status only.Conclusion: Survival in resected pancreatic cancer is improving over time. Resection margin status is a key factor affecting recurrence patterns and prognosis. Given the poor recurrence-free survival in node station 16 metastasised patients, the rational for resection remains in doubt, and improved treatment strategies for this patient group is necessary.

BackgroundIn the recent phase III trial MPACT the combination of gemcitabine and nab-paclitaxel (Gem/NabP) showed increased overall survival compared to gemcitabine alone in the treatment of advanced pancreatic ductal adenocarcinoma (aPDA). Until now there has been limited information on the clinical benefit and toxicity of the combination regimen in a real world setting. In addition the value for patients with locally advanced rather than metastatic aPDA has been unclear, since the former category of patients was not included in the MPACT trial.MethodsA multicentre retrospective observational study in the South Eastern Region of Sweden was performed, with the first 75 consecutive patients diagnosed with aPDA (both locally advanced and metastatic disease) who received first-line treatment with Gem/NabP.ResultsIn the overall population median progression free survival (PFS) and overall survival (OS) were 5.2 (3.4-7.0 95% CI) and 10.9 (7.8-14.0 95% CI) months, respectively. Patients with metastatic disease displayed a median OS of 9.4 (4.9-13.9) and a median PFS of 4.5 (3.3-5.7) months whereas the same parameters in the locally advanced subgroup were 17.1 (7.6-26.6) and 6.8 (5.2-8.4) months, respectively. Grade 3-4 hematologic toxicity was recorded: Neutropenia, leukopenia, thrombocytopenia, and anaemia were observed in 23, 20, 5, and 4% of patients, respectively. Dose reductions were performed in 80% of the patients.ConclusionThis study confirms the effectiveness and safety of first-line Gem/NabP in both locally advanced and metastatic PDA in a real world setting.

Aims: One of the major drivers of the adoption of digital pathology in clinical practice is the possibility of introducing digital image analysis (DIA) to assist with diagnostic tasks. This offers potential increases in accuracy, reproducibility, and efficiency. Whereas stand-alone DIA has great potential benefit for research, little is known about the effect of DIA assistance in clinical use. The aim of this study was to investigate the clinical use characteristics of a DIA application for Ki67 proliferation assessment. Specifically, the human-in-the-loop interplay between DIA and pathologists was studied. Methods and results: We retrospectively investigated breast cancer Ki67 areas assessed with human-in-the-loop DIA and compared them with visual and automatic approaches. The results, expressed as standard deviation of the error in the Ki67 index, showed that visual estimation (eyeballing) (14.9 percentage points) performed significantly worse (P &lt; 0.05) than DIA alone (7.2 percentage points) and DIA with human-in-the-loop corrections (6.9 percentage points). At the overall level, no improvement resulting from the addition of human-in-the-loop corrections to the automatic DIA results could be seen. For individual cases, however, human-in-the-loop corrections could address major DIA errors in terms of poor thresholding of faint staining and incorrect tumour-stroma separation. Conclusion: The findings indicate that the primary value of human-in-the-loop corrections is to address major weaknesses of a DIA application, rather than fine-tuning the DIA quantifications.

AimReliably diagnosing or safely excluding serous tubal intraepithelial carcinoma (STIC), a precursor lesion of tubo-ovarian high-grade serous carcinoma (HGSC), is crucial for individual patient care, for better understanding the oncogenesis of HGSC, and for safely investigating novel strategies to prevent tubo-ovarian carcinoma. To optimize STIC diagnosis and increase its reproducibility, we set up a three-round Delphi study. Methods and resultsIn round 1, an international expert panel of 34 gynecologic pathologists, from 11 countries, was assembled to provide input regarding STIC diagnosis, which was used to develop a set of statements. In round 2, the panel rated their level of agreement with those statements on a 9-point Likert scale. In round 3, statements without previous consensus were rated again by the panel while anonymously disclosing the responses of the other panel members. Finally, each expert was asked to approve or disapprove the complete set of consensus statements. The panel indicated their level of agreement with 64 statements. A total of 27 statements (42%) reached consensus after three rounds. These statements reflect the entire diagnostic work-up for pathologists, regarding processing and macroscopy (three statements); microscopy (eight statements); immunohistochemistry (nine statements); interpretation and reporting (four statements); and miscellaneous (three statements). The final set of consensus statements was approved by 85%. ConclusionThis study provides an overview of current clinical practice regarding STIC diagnosis amongst expert gynecopathologists. The experts consensus statements form the basis for a set of recommendations, which may help towards more consistent STIC diagnosis.

Metastasis occurs frequently after resection of pancreatic cancer (PaC). In this study, we hypothesized that multi-parametric analysis of pre-metastatic liver biopsies would classify patients according to their metastatic risk, timing and organ site. Liver biopsies obtained during pancreatectomy from 49 patients with localized PaC and 19 control patients with non-cancerous pancreatic lesions were analyzed, combining metabolomic, tissue and single-cell transcriptomics and multiplex imaging approaches. Patients were followed prospectively (median 3 years) and classified into four recurrence groups; early (&lt;6 months after resection) or late (&gt;6 months after resection) liver metastasis (LiM); extrahepatic metastasis (EHM); and disease-free survivors (no evidence of disease (NED)). Overall, PaC livers exhibited signs of augmented inflammation compared to controls. Enrichment of neutrophil extracellular traps (NETs), Ki-67 upregulation and decreased liver creatine significantly distinguished those with future metastasis from NED. Patients with future LiM were characterized by scant T cell lobular infiltration, less steatosis and higher levels of citrullinated H3 compared to patients who developed EHM, who had overexpression of interferon target genes (MX1 and NR1D1) and an increase of CD11B(+) natural killer (NK) cells. Upregulation of sortilin-1 and prominent NETs, together with the lack of T cells and a reduction in CD11B(+) NK cells, differentiated patients with early-onset LiM from those with late-onset LiM. Liver profiles of NED closely resembled those of controls. Using the above parameters, a machine-learning-based model was developed that successfully predicted the metastatic outcome at the time of surgery with 78% accuracy. Therefore, multi-parametric profiling of liver biopsies at the time of PaC diagnosis may determine metastatic risk and organotropism and guide clinical stratification for optimal treatment selection.&lt;br /&gt;

Tumor budding is a promising and cost-effective biomarker with strong prognostic value in colorectal cancer. However, challenges related to interobserver variability persist. Such variability may be reduced by immunohistochemistry and computer-aided tumor bud selection. Development of computer algorithms for this purpose requires unequivocal examples of individual tumor buds. As such, we undertook a large-scale, international, and digital observer study on individual tumor bud assessment. From a pool of 46 colorectal cancer cases with tumor budding, 3000 tumor bud candidates were selected, largely based on digital image analysis algorithms. For each candidate bud, an image patch (size 256 x 256 mu m) was extracted from a pan cytokeratin-stained whole-slide image. Members of an International Tumor Budding Consortium (n = 7) were asked to categorize each candidate as either (1) tumor bud, (2) poorly differentiated cluster, or (3) neither, based on current definitions. Agreement was assessed with Cohens and Fleiss Kappa statistics. Fleiss Kappa showed moderate overall agreement between observers (0.42 and 0.51), while Cohens Kappas ranged from 0.25 to 0.63. Complete agreement by all seven observers was present for only 34% of the 3000 tumor bud candidates, while 59% of the candidates were agreed on by at least five of the seven observers. Despite reports of moderate-to-substantial agreement with respect to tumor budding grade, agreement with respect to individual pan cytokeratin-stained tumor buds is moderate at most. A machine learning approach may prove especially useful for a more robust assessment of individual tumor buds.

Tumor budding (TB), the presence of single cells or small clusters of up to 4 tumor cells at the invasive front of colorectal cancer (CRC), is a proven risk factor for adverse outcomes. International definitions are necessary to reduce interobserver variability. According to the current international guidelines, hotspots at the invasive front should be counted in hematoxylin and eosin (H & E)-stained slides. This is time-consuming and prone to interobserver variability; therefore, there is a need for computer-aided diagnosis solutions. In this study, we report an artificial intelligence-based method for detecting TB in H & E-stained whole slide images. We propose a fully automated pipeline to identify the tumor border, detect tumor buds, characterize them based on the number of tumor cells, and produce a TB density map to identify the TB hotspot. The method outputs the TB count in the hotspot as a computational biomarker. We show that the proposed automated TB detection workflow performs on par with a panel of 5 pathologists at detecting tumor buds and that the hotspot-based TB count is an independent prognosticator in both the univariate and the multivariate analysis, validated on a cohort of n 1/4 981 patients with CRC. Computer-aided detection of tumor buds based on deep learning can perform on par with expert pathologists for the detection and quantification of tumor buds in H & E-stained CRC histopathology slides, strongly facilitating the introduction of budding as an independent prognosticator in clinical routine and clinical trials. & COPY; 2023 THE AUTHORS. Published by Elsevier Inc. on behalf of the United States & Canadian Academy of Pathology. This is an open access article under the CC BY license (http://creativecommons.org/ licenses/by/4.0/).

In colorectal cancer (CRC), artificial intelligence (AI) can alleviate the laborious task of characterization and reporting on resected biopsies, including polyps, the numbers of which are increasing as a result of CRC population screening programs ongoing in many countries all around the globe. Here, we present an approach to address two major challenges in the automated assessment of CRC histopathology whole-slide images. We present an AI-based method to segment multiple (n=14 ) tissue compartments in the H &E-stained whole-slide image, which provides a different, more perceptible picture of tissue morphology and composition. We test and compare a panel of state-of-the-art loss functions available for segmentation models, and provide indications about their use in histopathology image segmentation, based on the analysis of (a) a multi-centric cohort of CRC cases from five medical centers in the Netherlands and Germany, and (b) two publicly available datasets on segmentation in CRC. We used the best performing AI model as the basis for a computer-aided diagnosis system that classifies colon biopsies into four main categories that are relevant pathologically. We report the performance of this system on an independent cohort of more than 1000 patients. The results show that with a good segmentation network as a base, a tool can be developed which can support pathologists in the risk stratification of colorectal cancer patients, among other possible uses. We have made the segmentation model available for research use on .

Tumor budding is a histopathological biomarker associated with metastases and adverse survival outcomes in colorectal carcinoma (CRC) patients. It is characterized by the presence of single tumor cells or small clusters of cells within the tumor or at the tumor-invasion front. In order to obtain a tumor budding score for a patient, the region with the highest tumor bud density must first be visually identified by a pathologist, after which buds will be counted in the chosen hotspot field. The automation of this process will expectedly increase efficiency and reproducibility. Here, we present a deep learning convolutional neural network model that automates the above procedure. For model training, we used a semi-supervised learning method, to maximize the detection performance despite the limited amount of labeled training data. The model was tested on an independent dataset in which human- and machine-selected hotspots were mapped in relation to each other and manual and machine detected tumor bud numbers in the manually selected fields were compared. We report the results of the proposed method in comparison with visual assessment by pathologists. We show that the automated tumor bud count achieves a prognostic value comparable with visual estimation, while based on an objective and reproducible quantification. We also explore novel metrics to quantify buds such as density and dispersion and report their prognostic value. We have made the model available for research use on the grand-challenge platform.

Low-intensity loading maintains or increases bone mass, whereas lack of mechanical loading and high-intensity loading decreases bone mass, possibly via the release of extracellular vesicles by mechanosensitive bone cells. How different loading intensities alter the biological effect of these vesicles is not fully understood. Dynamic fluid shear stress at low intensity (0.7 +/- 0.3 Pa, 5 Hz) or high intensity (2.9 +/- 0.2 Pa, 1 Hz) was used on mouse hematopoietic progenitor cells for 2 min in the presence or absence of chemical compounds that inhibit release or biogenesis of extracellular vesicles. We used a Receptor activator of nuclear factor kappa-Beta ligand-induced osteoclastogenesis assay to evaluate the biological effect of different fractions of extracellular vesicles obtained through centrifugation of medium from hematopoietic stem cells. Osteoclast formation was reduced by microvesicles (10 000x g) obtained after low-intensity loading and induced by exosomes (100 000x g) obtained after high-intensity loading. These osteoclast-modulating effects could be diminished or eliminated by depletion of extracellular vesicles from the conditioned medium, inhibition of general extracellular vesicle release, inhibition of microvesicle biogenesis (low intensity), inhibition of ESCRT-independent exosome biogenesis (high intensity), as well as by inhibition of dynamin-dependent vesicle uptake in osteoclast progenitor cells. Taken together, the intensity of mechanical loading affects the release of extracellular vesicles and change their osteoclast-modulating effect. The intensity of mechanical loading strongly affects bone remodeling by either formation of bone or resorption of bone. Low-intensity loading on bone cells releases microvesicles that reduce formation of bone-resorbing osteoclasts, while high-intensity loading on bone cells releases exosomes that induce formation of bone-resorbing osteoclasts. The graphical abstract was created with image

Improvements to patient care through the development of automated image analysis in pathology are restricted by the small image patch size that can be processed by convolutional neural networks (CNNs), when compared to the whole-slide image (WSI). Tile-by-tile processing across the entire WSI is slow and inefficient. While this may improve with future computing power, the technique remains vulnerable to noise from uninformative image areas. We propose a novel attention-inspired algorithm that selects image patches from informative parts of the WSI, first using a sparse randomised grid pattern, then iteratively re-sampling at higher density in regions where a CNN classifies patches as tumour. Subsequent uniform sampling across the enclosing region of interest (ROI) is used to mitigate sampling bias. Benchmarking tests informed the adoption of VGG19 as the main CNN architecture, with 79% classification accuracy. A further CNN was trained to separate false-positive normal epithelium from tumour epithelium, in a novel adaptation of a two-stage model used in brain imaging. These subsystems were combined in a processing pipeline to generate spatial distributions of classified patches from unseen WSIs. The ROI was predicted with a mean F1 (Dice) score of 86.6% over 100 evaluation WSIs. Several algorithms for evaluating tumour–stroma ratio (TSR) within the ROI were compared, giving a lowest root mean square (RMS) error of 11.3% relative to pathologists’ annotations, against 13.5% for an equivalent tile-by-tile pipeline. Our pipeline processed WSIs between 3.3x and 6.3x faster than tile-by-tile processing. We propose our attention-based sampling pipeline as a useful tool for pathology researchers, with the further potential for incorporating additional diagnostic calculations. © 2022 The Authors

ObjectivesThe median survival in glioblastoma (GBM) patients used to be less than 1year. Surgical removal of the tumor with subsequent concomitant radiation/temozolomide (the Stupp regimen) has been shown to prolong survival. The Stupp protocol was implemented in the county of Jonkoping in 2006. The purpose of this study was to examine if the Stupp treatment has prolonged overall survival, in an unselected patient cohort with histologically verified GBM. Material and MethodThis study includes all patients from the county of Jonkoping, with a diagnosis of GBM from January 2001 to December 2012. Patients were divided into 2 cohorts, 2001-2005 and 2006-2012, that is before and after implementation of the Stupp regimen. By reviewing the medical case notes, the dates of the histological diagnosis and of death were identified. The median and mean overall survival and Kaplan-Meier survival analysis were calculated and compared between the 2 cohorts. ResultsThe mean survival was 110days longer in the cohort treated according to the Stupp regimen. Four patients in the 2006-2012 cohort and 1 patient in the 2001-2005 cohort are still alive. When comparing survival in patients with radical surgery vs biopsy, those that underwent radical surgery survived longer. The significance was slightly greater in the 2001-2005 cohort (mean 163 vs 344days, Pamp;lt;.001) than in the 2006-2012 cohort (mean 220 vs 397days, P=.02). ConclusionSurvival significantly improved after the implementation of the Stupp regimen in the study region of Sweden.

The Gleason score is the most important prognostic marker for prostate cancer patients, but it suffers from significant observer variability. Artificial intelligence (AI) systems based on deep learning can achieve pathologist-level performance at Gleason grading. However, the performance of such systems can degrade in the presence of artifacts, foreign tissue, or other anomalies. Pathologists integrating their expertise with feedback from an AI system could result in a synergy that outperforms both the individual pathologist and the system. Despite the hype around AI assistance, existing literature on this topic within the pathology domain is limited. We investigated the value of AI assistance for grading prostate biopsies. A panel of 14 observers graded 160 biopsies with and without AI assistance. Using AI, the agreement of the panel with an expert reference standard increased significantly (quadratically weighted Cohens kappa, 0.799 vs. 0.872;p = 0.019). On an external validation set of 87 cases, the panel showed a significant increase in agreement with a panel of international experts in prostate pathology (quadratically weighted Cohens kappa, 0.733 vs. 0.786;p = 0.003). In both experiments, on a group-level, AI-assisted pathologists outperformed the unassisted pathologists and the standalone AI system. Our results show the potential of AI systems for Gleason grading, but more importantly, show the benefits of pathologist-AI synergy.

Through a community-driven competition, the PANDA challenge provides a curated diverse dataset and a catalog of models for prostate cancer pathology, and represents a blueprint for evaluating AI algorithms in digital pathology. Artificial intelligence (AI) has shown promise for diagnosing prostate cancer in biopsies. However, results have been limited to individual studies, lacking validation in multinational settings. Competitions have been shown to be accelerators for medical imaging innovations, but their impact is hindered by lack of reproducibility and independent validation. With this in mind, we organized the PANDA challenge-the largest histopathology competition to date, joined by 1,290 developers-to catalyze development of reproducible AI algorithms for Gleason grading using 10,616 digitized prostate biopsies. We validated that a diverse set of submitted algorithms reached pathologist-level performance on independent cross-continental cohorts, fully blinded to the algorithm developers. On United States and European external validation sets, the algorithms achieved agreements of 0.862 (quadratically weighted kappa, 95% confidence interval (CI), 0.840-0.884) and 0.868 (95% CI, 0.835-0.900) with expert uropathologists. Successful generalization across different patient populations, laboratories and reference standards, achieved by a variety of algorithmic approaches, warrants evaluating AI-based Gleason grading in prospective clinical trials.

The recent years have been characterised by a rapid development of whole slide imaging (WSI) especially in its applications to histology. The application of WSI technology to cytology is less common because of technological problems related to the three-dimensional nature of cytology preparations (which requires capturing of z-stack information, with an increase in file size and usability issues in viewing cytological preparations). The aim of this study is to provide a review of the literature on the use of digital cytology and provide an overview of cytological applications of WSI in current practice as well as identifying areas for future development.

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Context: Within digital pathology, digitalization of the grossing procedure has been relatively underexplored in comparison to digitalization of pathology slides. 

Aims: Our investigation focuses on the interaction design of an augmented reality gross pathology workstation and refining the interface so that information and visualizations are easily recorded and displayed in a thoughtful view. 

Settings and Design: The work in this project occurred in two phases: the first phase focused on implementation of an augmented reality grossing workstation prototype while the second phase focused on the implementation of an incremental prototype in parallel with a deeper design study. 

Subjects and Methods: Our research institute focused on an experimental and “designerly” approach to create a digital gross pathology prototype as opposed to focusing on developing a system for immediate clinical deployment. 

Statistical Analysis Used: Evaluation has not been limited to user tests and interviews, but rather key insights were uncovered through design methods such as “rapid ethnography” and “conversation with materials”. 

Results: We developed an augmented reality enhanced digital grossing station prototype to assist pathology technicians in capturing data during examination. The prototype uses a magnetically tracked scalpel to annotate planned cuts and dimensions onto photographs taken of the work surface. This article focuses on the use of qualitative design methods to evaluate and refine the prototype. Our aims were to build on the strengths of the prototype's technology, improve the ergonomics of the digital/physical workstation by considering numerous alternative design directions, and to consider the effects of digitalization on personnel and the pathology diagnostics information flow from a wider perspective. A proposed interface design allows the pathology technician to place images in relation to its orientation, annotate directly on the image, and create linked information. 

Conclusions: The augmented reality magnetically tracked scalpel reduces tool switching though limitations in today's augmented reality technology fall short of creating an ideal immersive workflow by requiring the use of a monitor. While this technology catches up, we recommend focusing efforts on enabling the easy creation of layered, complex reports, linking, and viewing information across systems. Reflecting upon our results, we argue for digitalization to focus not only on how to record increasing amounts of data but also how these data can be accessed in a more thoughtful way that draws upon the expertise and creativity of pathology professionals using the systems.

Context.-Flexible working at diverse or remote sites is a major advantage when reporting using digital pathology, but currently there is no method to validate the clinical diagnostic setting within digital microscopy. Objective.-To develop a preliminary Point-of-Use Quality Assurance (POUQA) tool designed specifically to validate the diagnostic setting for digital microscopy. Design.-We based the POUQA tool on the red, green, and blue (RGB) values of hematoxylin-eosin. The tool used 144 hematoxylin-eosin-colored, 5x5-cm patches with a superimposed random letter with subtly lighter RGB values from the background color, with differing levels of difficulty. We performed an initial evaluation across 3 phases within 2 pathology departments: 1 in the United Kingdom and 1 in Sweden. Results.-In total, 53 experiments were conducted across all phases resulting in 7632 test images viewed in all. Results indicated that the display, the users visual system, and the environment each independently impacted performance. Performance was improved with reduction in natural light and through use of medical-grade displays. Conclusions.-The use of a POUQA tool for digital microscopy is essential to afford flexible working while ensuring patient safety. The color-contrast test provides a standardized method of comparing diagnostic settings for digital microscopy. With further planned development, the color-contrast test may be used to create a "Verified Login" for diagnostic setting validation.

Purpose: As pathology departments around the world contemplate digital microscopy for primary diagnosis, making an informed choice regarding display procurement is very challenging in the absence of defined minimum standards. In order to help inform the decision, we aimed to conduct an evaluation of displays with a range of technical specifications and sizes. Approach: We invited histopathologists within our institution to take part in a survey evaluation of eight short-listed displays. Pathologists reviewed a single haematoxylin and eosin whole slide image of a benign nevus on each display and gave a single score to indicate their preference in terms of image quality and size of the display. Results: Thirty-four pathologists took part in the display evaluation experiment. The preferred display was the largest and had the highest technical specifications (11.8-MP resolution, 2100 cd/m(2) maximum luminance). The least preferred display had the lowest technical specifications (2.3-MP resolution, 300 cd/m(2) maximum luminance). A trend was observed toward an increased preference for displays with increased luminance and resolution. Conclusions: This experiment demonstrates a preference for large medical-grade displays with the high luminance and high resolution. As cost becomes implicated in procurement, significantly less expensive medical-grade displays with slightly lower technical specifications may be the most cost-effective option. (C) 2020 Society of Photo-Optical Instrumentation Engineers (SPIE)

Digital microscopy produces high resolution digital images of pathology slides. Because no acceptable and effective control of color reproduction exists in this domain, there is significant variability in color reproduction of whole slide images. Guidance from international bodies and regulators highlights the need for color standardization. To address this issue, we systematically measured and analyzed the spectra of histopathological stains. This information was used to design a unique color calibration slide utilizing real stains and a tissue-like substrate, which can be stained to produce the same spectral response as tissue. By closely mimicking the colors in stained tissue, our target can provide more accurate color representation than film-based targets, whilst avoiding the known limitations of using actual tissue. The application of the color calibration slide in the clinical setting was assessed by conducting a pilot user-evaluation experiment with promising results. With the imminent integration of digital pathology into the routine work of the diagnostic pathologist, it is hoped that this color calibration slide will help provide a universal color standard for digital microscopy thereby ensuring better and safer healthcare delivery.

The current subjective histopathological assessment of cutaneous melanoma is challenging. The application of image analysis algorithms to histological images may facilitate improvements in workflow and prognostication. To date, several individual algorithms applied to melanoma histological images have been reported with variations in approach and reported accuracies. Histological digital images can be created using a camera mounted on a light microscope, or through whole slide image (WSI) generation using a whole slide scanner. Before any such tool could be integrated into clinical workflow, the accuracy of the technology should be carefully evaluated and summarised. Therefore, the objective of this review was to evaluate the accuracy of existing image analysis algorithms applied to digital histological images of cutaneous melanoma.Database searching of PubMed and Embase from inception to 11th March 2022 was conducted alongside citation checking and examining reports from organisations. All studies reporting accuracy of any image analysis applied to histological images of cutaneous melanoma, were included. The reference standard was any histological assessment of haematoxylin and eosin-stained slides and/or immunohistochemical staining. Citations were independently deduplicated and screened by two review authors and disagreements were resolved through discussion. The data was extracted concerning study demographics; type of image analysis; type of reference standard; conditions included and test statistics to construct 2 x 2 tables. Data was extracted in accordance with our protocol and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Diagnostic Test Accuracy (PRISMA-DTA) Statement. A bivariate random-effects meta-analysis was used to estimate summary sensitivities and specificities with 95% confidence intervals (CI). Assessment of methodological quality was conducted using a tailored version of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. The primary outcome was the pooled sensitivity and specificity of image analysis applied to cutaneous melanoma histological images. Sixteen studies were included in the systematic review, representing 4,888 specimens. Six studies were included in the meta-analysis. The mean sensitivity and specificity of automated image analysis algorithms applied to melanoma histological images was 90% (CI 82%, 95%) and 92% (CI 79%, 97%), respectively. Based on limited and heterogeneous data, image analysis appears to offer high accuracy when applied to histological images of cutaneous melanoma. However, given the early exploratory nature of these studies, further development work is necessary to improve their performance.